Project Summary/Abstract Glioblastomas (GBM) are devastating central nervous system tumors that are associated with an immunosuppressive network impacting the tumor microenvironment, bone marrow and peripheral blood compartments. The development of novel markers of cancer immunity have not kept pace with breakthroughs in our understanding of cancer-associated inflammation and its relationship with abnormal hematopoiesis and the production of myeloid derived suppressor cells. This gap in our understanding is a recognized high priority in the new era of cancer immunotherapy. The Cancer Moonshot blue ribbon panel recommended as a key actionable goal ?to develop approaches to overcome an obstructive, immune-suppressive tumor environment in both children and adults?. Our project addresses this important goal by developing and testing a highly innovative approach for measuring immunosuppression in GBM patients. Our powerful method for immune profiling that is based on unique immune cell DNA methylation fingerprints is more reproducible, and less intrusive and costly than current methods. Using this novel immunomethylomic approach for immune profiling in Aim 1 we will serially assess immune status in a large group of patients with newly diagnosed GBM from their initial diagnosis through their surgery, radiation and chemotherapy treatments. At each of 5 time points we will assess each patient's levels of immunosuppressive myeloid derived suppressor and other cell types through the peripheral blood immune profile. To identify clinical correlates of treatment response and tumor recurrence at each point we will also assess each patient's MRI scans. In Aim 2 we will then assess the prognostic value of methylation generated immune profiles (myeloid derived suppressor cells, CD4, CD8, T- cells, B-cells, NK, monocytes, and neutrophils) and other factors in GBM patient survival and progression. In Aim 3 we will evaluate how the new information on patient immune profiles can influence clinical decision making. We will build comprehensive statistical models that include relevant clinical variables to predict patient survival and tumor progression as well as combined models that include both immune factors and clinical variables. Rigorous comparisons of purely clinical versus combined models (which include immune factors) will be evaluated and will reveal how immune profiles can improve GBM outcome prediction. The end result of these studies will enable clinicians and patients to better understand their prognosis and improve risk stratification for future clinical trials. Improved predictions of tumor progression will help to avoid unnecessary interventions that may be invasive and potentially harmful. Incorporation of DNA based assessment of immune factors in prognostic models of GBM survival and progression will provide a major advance in patient management and outcomes.